MCDC Legacy
Supporting Instruction with Real Data Problems
Big Picture
Through MCDC practicums and DAUs (Data Application for Undergraduates) students and faculty have worked on a wide range of data rich projects for various community partners.
Goal
Take these data projects and package them into open lesson plans for instructors to use at various points in a data science course or curriculum.
Re-package the data collection, wrangling, and visualization steps from a project into lessons. Providing a beginning students with a sense of how to breakdown and tackle data projects.
Design lessons that attempt the data projects again.
Create a data repository where instructors can freely access the data and use them in examples or their own lessons. Also, submit to existing data repositories.
The Basics
Instructional Materials are being developed and organized by Professors Lizhen Shi and Arend M Kuyper
GitHub Organization MDCD-Instructional-Materials will host the developed materials which will all have their own GitHub repositories with all supporting documentation
Plan to license under CC BY-SA 4.0 — Creative Commons Attribution-ShareAlike 4.0 International CC BY-SA 4.0
Data Projects
Some of the data is publicly avialable.
Obtaining permission from a few of the projects.
We plan to make use of as many projects as possible!
Example Lessons
Lessons for Data Science Pathway Courses — Developed by Professor Shi
Results & data from the Equiticity Project
Feature Engineering and Time Series Aggregation with Divvy Data
Geospatial Visualization with GeoPandas and Folium
Enriching Divvy Data with External Datasets for Socio-Spatial Analysis
Distribution Plan
Complete a basic/self-contained release by end of Fall 2025
Post/announce on ASA teaching forums and/or CAUSE
Submit to teaching journals
